Simulation is a kind of modelling which is useful for wide range of problems and
situations. It has applications to both quantitative and qualitative problems with either very
good data, or very little data. It has important implications for disciplines such as social
anthropology which are basically non-experimental, providing a means of exploring
problems which could never be observed to order. Simulation is not a panacea for all of
our problems, but it can be an important tool for the social researcher aware of its
limitations.

Simulations are distinguished from other kinds of models more in terms of goal than form.
Simulations are typically used for problems which are seen as complex and intractable,
where no direct means of evaluation is known or the conventional means of evaluation is
extremely difficult to execute, or which requires interactive decisions by the investigator
during the course of the model.

Simulation can be defined in either a broad or narrow sense. In the narrow sense
simulation is a model where we are attempting to describe the behaviour of a system by
incrementally and interactionally applying a number of models against some starting
situation. In the broader sense, it is any kind of computer model within which some
structure is being modified along one or more dimensions. In the usual case one dimension
is time, but this is neither sufficient nor necessary for a simulation; it is the modelling of
any complex system where observation of change, or an incremental process, is central.
Both of these descriptions have in common the modelling of some structure under
modification or transformation; the behaviour of some data object along one or more
dimensions of change.

Traditionally simulation has been a technique used for quantitative analysis. As with
computing techniques in general this is due to the historical development of computing and
constraints on our knowledge of how to represent models and information of a qualitative
and symbolic form. Designing a simulation involves translating the essential aspects of
pre-existing models into a form which can be implemented on a computer so that we can
monitor the interaction of the models.

In social anthropology the most common (and successful) simulations have been based on
the interaction of models of prescriptive or preferential marriage, incest or other social
phenomena with either demographic models or ecological models (or both) (Kunstadter et
al 1963; Hammel and Gilbert 1965; Randolph and Coult 1965; MacCluer and Dyke 1976;
Black 1978; Relethford 1981; Buchler et al. 1986). The fundamental idea underlying these
simulations is to investigate the performance of social models in context with 'well-
understood' models, including the ethnographic model of collection.

Although simulations can be quite abstract and analytic, most anthropologists tend to
favour those which are fairly concrete. One reason for this is the emphasis of social
anthropology on structural relationships between individuals. If you are investigating the
feasibility of literal prescribed matrilateral cross-cousin marriage (c.f. Kundstater et al.
1963), then you must usually simulate a population as a set of people, not as a simple
aggregate. Each simulated person must have at least a mother and father, an age, a gender,
a marital status, and be subject to birth, marriage and death, and have, in some cases, a
history.

A simulation animates our models to produce data which we can use to evaluate these
models. This is of course possible to do without computers, but is a very time consuming
effort. Although most simulations have been applied to theoretical situations where
simulation was most useful precisely because it was not possible to observe these directly.
In the past few years simulations have been applied back to the field with promising
results.

Lansing (1991) describes a simulation which resulted from his fieldwork in Bali regarding
the role of water temples and the rituals associated with these and the regulation and
conservation of irrigation water for rice cultivation, and more controversially, their role in
pest control. Although a large part of the simulation related to ecological parameters, the
overall significance depended heavily on ethnographic data relating to how the water
temples functioned ritually as well, and how information flowed from the water temples to
the peasants who used irrigation water for their crops. It appears that among the results of
the simulation project was providing a basis for reversing official policy towards the water
temple system by the state and development agencies, which are now recognised by the
state and 'have regained informal control of cropping patterns in most of Bali'. (Lansing
1991:125)

Kippen (1988) applied a novel version of simulation, using a production system/expert
system to represent indigenous knowledge about improvising tabla music, animated
this model, creating not a literal set of recordings, but an improvisational 'performance' by
Kippen's model; literally something new but conforming to a pattern which his expert
consultants (tabla musicians) could make judgements about, criticise, and set a context for
Kippen to elicit new information on which to base modifications to the expert system
rules.

In the past we could argue that there was no real way to produce a directly testable model.
We can not yet produce formally provable models, but there is no reason, though, why at
a micro-level, we cannot make statements about what we believe we know, and evaluate
this with respect to what we think should be the outcome. Analysis should at least be
subjectable to a test of the internal consistency of the representation, regardless of how we
want to argue about the external reliability or lack thereof.